In anup50695/RtutoR: Shiny Apps for Plotting and Exploratory Analysis

Plotting App for ggplot2

You can view a demo of this app here and here

Overview

This app provides an automated interface for generating plots using the ggplot2 package. This first version of the app includes 10 different plot types along with options to manipulate specific aesthetics and controls related to each plot type (NOTE: ggplot2 provides an extremely rich and extensive set of aesthetics and controls to manipulate each aspect of a particular plot. While the list of aesthetics and controls provided by the app is fairly comprehensive, its by no means exhaustive and does not cover all the various options that ggplot2 provides. Secondly, this first version of the app includes only 10 different plot types while ggplot2 supports more than 35 different plots)

Launching the Plotter

launch_plotter(list(iris = iris, mtcars = mtcars))

Usage

The app can be used as follows:

The app is launched by invoking the launch_plotter(list_of_datasets) function. list of datasets should include the datasets that should be made available for selection by the app. If this argument is left blank, by default the iris and mtcars dataset is made availble for selection
Select a dataset from the Select Data tab (in case of multiple datasets being passed while paunching the app)
Each dataset should have valid column names that can be selected (as x and y variables) for generating a plot. This can be selected from the Variable & Geom type tab. Multiple layers can also be added to the plot by adjusting the Add additional layers slider
Depending on the variable type, a set of recommended plots is displayed under the plot selector dropdown (For example, if both x & y variables are numeric, plot types such as geom_point, geom_smooth etc is displayed). However, the entire set of 10 available plot types can be displayed by clicking on the Show all plots button
Set aesthetics tab provides option to manipulate plot specific aesthetics and controls. Aesthetics can be manipulated either directly or by mapping an aesthetic to a variable. Both options are supported by the app
Plots can be made interactive by clicking on the Switch ON interactivity button (and this can be turned off by clicking on the button again). Interactive plots are generated using the plotly package
Finally, the Other Plot Controls tab provides other options and controls such as Changing plot themes, Color palettes etc.